Re: Effect Size and Sample Size

On Jan 17, 3:33 pm, beginner1....@xxxxxxxxxxx wrote:
Thank you all for the very informative responses! I guess I do still
have the same question. It was posed that I should first determine
the effect size I wish to detect and then determine the sample size.
This is what brought up the original post in the first place. I was
determinig my effect size using Cohen's d - (difference between groups/
pool sd), where the data was based off of a N=4 (2 per group).
Because I did not think it would be appropriate to look at weather the
data was normally distributed (i.e., kurtosis, skewness) as it was
only 2 per group, I was wondering if this was indeed the case?
Perhaps the answer lies somewhere in this post, but it wasn't very
clear to me. Given that I have the data of N=4, would anyone argue
that I should not use Cohen's d to calculate effect size? I think the
argument would be in that because there are only 2 per group, the true
mean and true variability in the data is not established, thus may
affect the effect size calculation. I would like to collect more
data, and assuming the data fits the assumptions of a t-test, I would
run a t-test on a larger sample size. But, I would like to calculate
a sample size to do that, and since I do not have a larger sample to
pull means and sds from, I am trying to use the N=4 that I currently
have. Any recommendations?


Russell Lenth argues that using standardized effect sizes in sample
size estimation (or power analysis) can be problematic. Here is a
short article:

http://www.math.uiowa.edu/~rlenth/Power/2badHabits.pdf

The arguments Lenth offers apply even when the standardized effect
sizes are derived from large samples.

--
Bruce Weaver
bweaver@xxxxxxxxxxxx
www.angelfire.com/wv/bwhomedir
"When all else fails, RTFM."
.